Poverty incidence of farm households under differential access to water and exogenous prices: A Study in the Kirindi Oya Irrigation and Settlement Project

Abstract

Approximately 40% of global agricultural production relies on irrigation, which is a critical shared resource for increasing agricultural output, with surface irrigation being the most prevalent method. The Kirindi Oya Irrigation and Settlement Project (KOISP), which is a significant surface gravity irrigation system in the Hambantota District of Southern Sri Lanka, has well-established evidence of income disparities among farm households as a result of differential access to irrigation water. The initial focus of this study is to examine the prevalence of inequality in the distribution of irrigation water among farms, along with the incidence of income poverty. Additionally, the study aims to investigate the impact on poverty incidence resulting from changes in the supply of irrigation water quantities and exogenous market prices of inputs and outputs related to rice cultivation. The theoretical basis is the model of profit-maximising farm households. A secondary data source and a previously estimated production function were used to simulate production, net farm incomes, and poverty incidences. The baseline for the measure of water inequality is the Department of Agriculture's recommendation for minimum irrigation water requirement for paddy at the vegetative phase. The base period scenario (2006/07) was compared with the current period scenario (2020/21). The study's results showed that there were significant discrepancies in the amount of water received by farmers across different seasons and subareas of the system (P<0.05), with approximately 60% of farmers in the New Irrigation Area (NIA) having limited access to water during both cultivation seasons. The average water quantity received in the Old Irrigated Area (OIA) was 17% higher than the NIA. Household income increases with every unit of additional water received (P<0.05). The result of the binary logistic regression indicated that the water access (P<0.05), exogenous prices; agrochemicals (P<0.05); machinery (P<0.05), seeds (P<0.05) and rice (P<0.05) significantly influence the net income and the poverty status of households. Additional water allocation caused an apparent reduction in the poverty incidence in NIA. Changes to exogenous prices caused a distinct reduction in poverty incidence in both seasons of the current period (2020/21), which was more prominent in Maha, and a higher number of poor households were in OIA compared to NIA.